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Journal of Applied Sciences and Environmental Management
World Bank assisted National Agricultural Research Project (NARP) - University of Port Harcourt
ISSN: 1119-8362
Vol. 14, No. 2, 2010, pp. 81-85
Bioline Code: ja10032
Full paper language: English
Document type: Research Article
Document available free of charge

Journal of Applied Sciences and Environmental Management, Vol. 14, No. 2, 2010, pp. 81-85

 en Integrating Linear Programming and Analytical Hierarchical Processing in Raster-GIS to Optimize Land Use Pattern at Watershed Level
Fallah Shamsi, S.R.

Abstract

It is very important to develop an optimum land use pattern, in accord with ecological and economic constraints. However, studies indicate capability of linear programming to optimize allocation problems, land use planning is dealing with handling spatial information, and Linear Programming has not been developed for. To handle spatial Data leads to use Geographical Information Systems. Study area is about 28000 ha of Keleibar-Chai Watershed, located in eastern Azerbaijan, Iran. Socio-economic information collected through a two-stage survey of 19 villages, including 300 samples. Thematic maps also have summarized Ecological factors, including physical and economic data. A comprehensive Linear Programming model established, including 106 variables and 43 ecological-socio-economic constraints. Land capability and suitability evaluation accomplished using ecological factors and Comparative Advantages of the uses and the factors, respectively. Analytical Hierarchical Process followed to determine the Comparative Advantages. The allocation process employs a Multi-Criteria Evaluation and a Multi-Objective Land Allocation procedure. Hereby, Linear Programming optimum pattern entered in the process. IDRISIW2.008 Raster-GIS used for doing the spatial analysis. So, 5192, 1019, 94 and 9354 ha of rain-fed barley, walnut orchard, park and rangeland assessed and allocated in the pattern respectively. The model is easily retrievable; however, plenty of data is required. Integrating a non-linear model into GIS is also recommended. @ JASEM

 
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